About OMICS Group

OMICS Group International is an amalgamation of Open Access publications and worldwide international science conferences and events. Established in the year 2007 with the sole aim of making the information on Sciences and technology ‘Open Access’, OMICS Group publishes 400 online open access scholarly journals in all aspects of Science, Engineering, Management and Technology journals. OMICS Group has been instrumental in taking the knowledge on Science & technology to the doorsteps of ordinary men and women. Research Scholars, Students, Libraries, Educational Institutions, Research centers and the industry are main stakeholders that benefitted greatly from this knowledge dissemination. OMICS Group also organizes 300 International conferences annually across the globe, where knowledge transfer takes place through debates, round table discussions, poster presentations, workshops, symposia and exhibitions.

About OMICS Group Conferences

OMICS Group International is a pioneer and leading science event

organizer, which publishes around 400 open access journals and

conducts over 300 Medical, Clinical, Engineering, Life Sciences,

Pharma scientific conferences all over the globe annually with the

support of more than 1000 scientific associations and 30,000 editorial

board members and 3.5 million followers to its credit.

OMICS Group has organized 500 conferences, workshops and

national symposiums across the major cities including San

Francisco, Las Vegas, San Antonio, Omaha, Orlando, Raleigh, Santa

Clara, Chicago, Philadelphia, Baltimore, United Kingdom, Valencia,

Dubai, Beijing, Hyderabad, Bengaluru and Mumbai.

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Source: Festo AG

MEASURING USER EXPERIENCE DURING A DRIVING

SIMULATION WITH MINARGUS

Automobile Engineering September 01-02, 2015

Valencia, Spain

Maik Auricht1

Rainer Stark2

1 Technische Universität Berlin

² Fraunhofer IPK, Berlin

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Fraunhofer-Gesellschaft Institute for Production

Systems and Design Technology (IPK)

Technische Universität Berlin School of Mechanical Engineering

and Transportation Systems (IWF)

Virtual Product Creation Prof. Dr.-Ing. R. Stark

Industrial Information Technology Prof. Dr.-Ing. R. Stark

Major research fields: Product development methods and processes

Product modelling and functional validation

Intuitive interaction with virtual prototypes

Information management for product creation

Digital manufacturing operations and factory processes

Source of Picture: Fraunhofer IPK, Alina Goldberg

Product modelling and functional validation

Intuitive interaction with virtual prototypes

Product development methods and processes

Information management for product creation

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Motivation

„With its analysis of more than 300 innovations Oliver Wyman shows that, among other

hybrid drives, sequential multi-stage turbocharger, LEDs, intelligent driver-machine

interface and electromagnetic brake technologies have the potential to success.

Electronics continues to be the central 'enabler' and drivers for 60 percent of all

innovations, with the focus shifted from individual applications to system

applications that combine multiple components. As new features are often

created by an intelligent combination of existing components and modules.

Almost all the core features of the car will improve: Fuel efficiency (up to 30 percent),

emissions, active and passive safety, connectivity and infotainment, vehicle dynamics

and performance characteristics, comfort, flexibility and space - while improving cost-

benefit ratio for buyers . “

DANNENBERG, J.; BURGARD, J. (2007): 2015 car innovation - Innovationsmanagement in der

Automobilindustrie, Oliver Wyman (Hg.)

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Motivation

Almost every car is equipped with Advanced Driver Assistance Systems (ADAS)

It occurs, that drivers are not satisfied with the system

That can have different reasons:

A: Usability aspects (such as Effectiveness or Efficiency)

B: System does not work correctly (technical aspects)

C: System has interdependencies with other assistance systems (similar to B)

D: User experience issues (such as subjective feelings, motivational aspects)

There are different validation methods for the reason A-C in the early phases of the

product development process

However, there are no running validation methods for reason D

Reason D is more a validation problem rather than a verification problem*

*Verification: Are we building the system right? | Validation: Are we building the right system?

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Validation methods

for Advanced Driver

Assistance Systems

Structure of the presentation

User

Experience

Driving

Simulators State of the art

Results of the

questionnaire

Pilot questionnaire

MINARGUS: A new tool to

measure UX and control

the simulation

Development of a new tool to

perform User Experience tests

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Validation methods

for Advanced Driver

Assistance Systems

Structure of the presentation

User

Experience

Driving

Simulators State of the art

Results of the

questionnaire

Pilot questionnaire

MINARGUS: A new tool to

measure UX and control

the simulation

Development of a new tool to

perform User Experience tests

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State of the art Validation methods for Advanced Driver Assistance Systems (ADAS)

During development ADAS are tested with

different validation methods:

A: Model-in-the-Loop (MiL)*

B: Software-in-the-Loop (SiL)

C: Hardware-in-the-Loop (HiL)

D: Vehicle-in-the-Loop (ViL)

E: Field tests

During all tests, driving simulators are used in

different maturity levels

A

B

C

D

E

* Model in the Loop (MiL) is the simulation of an embedded system in an early development phase.

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DIN EN ISO 9001 © Fraunhofer, Technische Universität Berlin 9 / 21

Validation methods

for Advanced Driver

Assistance Systems

Structure of the presentation

User

Experience

Driving

Simulators State of the art

Results of the

questionnaire

Pilot questionnaire

MINARGUS: A new tool to

measure UX and control

the simulation

Development of a new tool to

perform User Experience tests

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State of the art

User Experience is more than Usability

It consideres emotions, subjective feelings,

aesthetic aspects, etc.

Questionnaires to measure the UX:

AttrakDiff

Affect Grid

mDES

VisAwi

Etc.

User Experience

“By “experience” we mean all the aspects of

how people use an interactive product: the

way it feels in their hands, how well they

understand how it works, how they feel about

it while they’re using it, how well it serves

their purposes, and how well it fits into the

entire context in which they are using it.” [1]

Source: [2]

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Validation methods

for Advanced Driver

Assistance Systems

Structure of the presentation

User

Experience

Driving

Simulators State of the art

Results of the

questionnaire

Pilot questionnaire

MINARGUS: A new tool to

measure UX and control

the simulation

Development of a new tool to

perform User Experience tests

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State of the art Driving simulators

Source: Festo

Source: Daimler

Source: DLR

Separation in static and dynamic simulators

Static simulators are often use in early phases (MiL)

Dynamic simulators provide G-forces and thus enhance

the user feeling

There are different price ranges depending on the

maturity:

Small driving seats (e.g. Festo Airmotion Ride 50k€)

Hydraulic hexapod-systems (e.g. DLR driving

simulator 2M€)

Full range simulators (e.g. Daimler 40M€)

The visualisation reaches from simple monitors up to

360° projection

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Validation methods

for Advanced Driver

Assistance Systems

Structure of the presentation

User

Experience

Driving

Simulators State of the art

Results of the

questionnaire

Pilot questionnaire

MINARGUS: A new tool to

measure UX and control

the simulation

Development of a new tool to

perform User Experience tests

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Pilot study

First pilot study

Exploratory questionnaire

5 closed questions

15 open questions

Participants:

36 experts (Virtual Product Creation)

Average age: 31

8 weeks duration

Setup

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Pilot study Results

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What is the big aim? Why do I need a new tool?

The aim is to change parameter during a driving simulation

Dependent variables are the components of UX

Configuration is complete if you have best UX-values

Driving simulation with Model-in-the-

Loop of the ADAS

Capturing the User

Experience

Parameter

changing of the

ADAS model

Optimal

parameter set

13

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Validation methods

for Advanced Driver

Assistance Systems

Structure of the presentation

User

Experience

Driving

Simulators State of the art

Results of the

questionnaire

Pilot questionnaire

MINARGUS: A new tool to

measure UX and control

the simulation

Development of a new tool to

perform User Experience tests

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DIN EN ISO 9001 © Fraunhofer, Technische Universität Berlin 18 / 21

MINARGUS

What is MINARGUS?

A tool which brings together the Engineering part

and the Physiological measurement

Why is it called MINARGUS?

MINARGUS = Minerva (Roman goddes of

wisdom) + Argus Panoptes (Greek mythology:

100-eyed giant)

What is MINARGUS capable of?

It allows the visualization of all measured data

and allows the direct parameter sweep within the

simulation model

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MINARGUS

1: Direct connection to

Matlab

2: Connection the User

Tracking Environment

3: Physiological

measurement system (PAR-

PORT)

4: Visualization of the

channels (e.g. EEG, EKG)

5,6: Standard functionalities

(save, jump to times etc)

7: Parameter changes of the

simulation model

3

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Change of validation process

Current development model

of the ADAS

Model import & implementation of parameters

Experiment

Evaluation

Start

Model optimization

End

n iterations

1 iteration cycle = ~ 2 h

The current process

Current development model

of the ADAS

Model import & implementation of parameters

Experiment

Start

Model optimization

End

MINARGUS

n iterations

1 iteration cycle = ~ 0.5 h

The improved process with MINARGUS

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MINARGUS: An example (1/2)

The developer defines the test and the parameters,

which need to be optimized

Using the example of the Traffic Jam Assist, defined

parameters can be the starting acceleration or the starting

delay

Both parameters are highly important for the UX: A high

starting acceleration and a short delay indicate an

aggressive driving behavior of the system and could cause

discomfort

Whereas a small starting acceleration and a long delay

could cause discomfort in terms of being forced to interact

because of the behind driving cars

These parameters are defined together with the

experimental designer

The experimental designer now builds up the UX test

with all its constraints (test procedure, test design,

questionnaires, etc.)

Traffic Jam Assist, Source: Bosch, 2014

Emotions, Source: KIT, 2014

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MINARGUS: An example (2/2)

After defining the parameters, they are then

integrated in the simulation model

The model and the simulation environment

must allow real-time simulation because of

adjustments to the parameters

In most cases there is a complete model of the

car and the environment (streets, other cars,

etc.)

In this stage testing can be conducted

The test subject drives a virtual car in a

simulator, which ideally covers all important

sense areas

Once the test has been performed, the results

can be evaluated. The model optimization is the

final step

Motion Desk, Source: dSpace, 2014

Automotive Simulation Model,

Source: dSpace, 2014

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Outlook

Festo Airmotion Ride

Digital Cube Test Center

Digital Cube Test Center

The presented tool shows a possible integration of

psychological measurement methods into existing

engineering validation methods

The usage of the tool can reduce the validation cycle

time by ~1,5h

Developers, validation engineers and human factor

experts work now more closer

Nevertheless the tool needs to be evaluated

In 2015 there will be a study to prove the functionalities

of the tool

The new tool will be evaluated within the Digital Cube

Test Center (DCTC) at the Technische Universität

Berlin

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Thanks.

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Sources

[1] Alben L. Quality of experience: defining the criteria for effective interaction design. interactions

1996;3:11–5

[2] Mahlke S. User Experience of Interaction with Technical Systems: Theories, Methods,

Empirical Results, and their Application to the Development of Interactive Systems. Dissertation.

Berlin; 2008.

[3] Auricht M, Dittrich E, Brandenburg S, Stark R. Engineering meet UX: Ingenieurstechnische

Absicherungsmethoden treffen auf User Experience Forschung. In: Dittrich E, Doria L, Gross A,

Günzler T, Smieszek H, editors. Proceedings of the 10. Berliner Werkstatt Mensch-Maschine-

Systeme: Grundlagen und Anwendungen der Mensch-Maschine-Interaktion. 10. Berliner Werkstatt

Mensch-Maschine-Systeme, 10th ed. Berlin: TU Berlin; 2013.